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test 2
On completion of training with MLflow logger enabled, the following exception is raised:
MlflowException: Invalid artifact path: '[/Shared/YOLOv8](https://file+.vscode-resource.vscode-cdn.net/Shared/YOLOv8)'.
Names may be treated as files in certain cases, and must not resolve to other names when treated as such.
This name would resolve to '[/Shared/YOLOv8](https://file+.vscode-resource.vscode-cdn.net/Shared/YOLOv8)
This arrises as logging artefacts attempts to write to '/Shared/YOLOv8', set below
experiment_name = trainer.args.project or '/Shared/YOLOv8'
Suggest using an alternative to '/Shared/YOLOv8'
Environment
Any
Minimal Reproducible Example
It is necessary to set a valid MLflow instance url and run model.train
os.environ["MLFLOW_TRACKING_URI"] = "https://dev-mlflow.bla.com/"
Additional
No response
Are you willing to submit a PR?
test issue 1
I'm trying Yolov8 with screen capture but it doesn't seem to work. I'm using the win32gui.GetDesktopWindow() to get the screenshot
Here my code
self.model = YOLO('yolov8n.pt')
frame = wincap.getScreenshot(detection_box)
results = self.model(frame)
print(results)
Here is what the output looks like.
[Ultralytics YOLO <class 'ultralytics.yolo.engine.results.Results'> instance
Ultralytics YOLO <class 'ultralytics.yolo.engine.results.Boxes'> masks
type: <class 'torch.Tensor'>
shape: torch.Size([0, 6])
dtype: torch.float32
original size: (270, 480)
]
When I try
print(results.boxes) or print(results.masks)
I get this error
AttributeError: 'list' object has no attribute 'boxes'
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